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ce-riffrec-feedback-analysis

Analyze Riffrec feedback recordings into structured reports with timestamps and events.

1|Updated Jun 2, 2026
Search Tags:#software development#requirements gathering#product feedback#feedback analysis#Riffrec
One-click install
npx skills add https://github.com/FFCfelps1/SGPPF_Maua --skill ce-riffrec-feedback-analysis-ffcfelps1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ce-riffrec-feedback-analysis
Source: https://github.com/FFCfelps1/SGPPF_Maua/tree/main/.gemini/skills/ce-riffrec-feedback-analysis
Command: npx skills add https://github.com/FFCfelps1/SGPPF_Maua --skill ce-riffrec-feedback-analysis-ffcfelps1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ffmpeg, openai-api-key, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms unstructured product feedback into structured data, facilitating analysis and requirements gathering for software development.

Core Features & Use Cases

  • Feedback Analysis: Processes Riffrec feedback recordings (video, audio, notes) to extract actionable insights.
  • Structured Output: Generates analysis reports with timestamps, events, and findings for review.
  • Use Case: After collecting user feedback using Riffrec, use this Skill to analyze the feedback and identify specific issues and requirements for development.

Quick Start

Analyze the Riffrec feedback file 'user-feedback.webm' using the ce-riffrec-feedback-analysis skill.

Frequently Asked Questions about ce-riffrec-feedback-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze product feedback recordings for software development requirements?▼

To analyze product feedback recordings for software development, this Skill processes video, audio, and notes to extract structured reports with timestamps, events, and findings suitable for review workflows.

What is the best way to turn raw user feedback into structured evidence?▼

Turning raw user feedback into structured evidence involves parsing media files and extracting transcripts, events, and moments, which this Skill automates by converting unstructured input into actionable development data.

Does feedback analysis require ffmpeg and an OpenAI API key?▼

Yes, feedback analysis requires ffmpeg and an OpenAI API key as dependencies to successfully parse media files and generate structured reports from raw recordings.

Can I use Python scripts to extract timestamps and events from video feedback?▼

Yes, you can use Python scripts to extract timestamps and events from video feedback, transforming unstructured media into structured output that facilitates requirements gathering.

What formats are supported for converting raw feedback into structured reports?▼

Supported formats for converting raw feedback into structured reports include video files like webm, audio, and text notes, all of which are processed to identify specific issues and requirements.

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